About the Role
As a Software Engineer on Applied AI, you’ll build, deploy, and operate systems that sit directly between frontier AI research and data delivery.
This is a high-ownership, deeply technical role. You’ll work through ill-defined problems, prototype quickly with researchers and customers, and take systems from early experiments to reliable, scalable production. You’ll own projects end-to-end: spanning requirements gathering, creating data creation pipelines, and improving model-adjacent infrastructure, while partnering closely with frontier AI labs and Mercor’s internal teams to ship high-impact applied AI solutions.
What You’ll Do
- Partner closely with frontier AI labs to understand their data, post-training, and evaluation needs
- Build and operate scalable data pipelines for post-training workflows and model evaluations
- Design and build scalable systems for synthetic data generation and data quality, and work directly with customers to understand requirements and develop technical solutions
- Prototype new data types, benchmarks, and evaluation frameworks
- Lead technical discussions with customers
What Makes This Role Different
- Direct frontier exposure. You’ll work closely with researchers at leading AI labs, building infrastructure that directly accelerates cutting-edge research.
- Coding + customer work. This role blends deep technical execution with customer interaction. Engineers who enjoy both building and communicating tend to thrive.
What We’re Looking For
- Strong backend engineering fundamentals in a modern language (Python, Go, Rust, etc.)
- Experience with model training and inference
- Strong grounding in statistical analysis and experimental design for measuring model performance and improvements
- Familiarity with evaluation methods for large language models
- Comfort working through ambiguity and shipping iteratively
You’re likely someone who
- Enjoys ownership and customer-facing problem solving
- Thinks entrepreneurially and moves quickly
- Balances speed with engineering rigor
- Communicates clearly with technical and non-technical users
Why Engineers Join
- Direct exposure to frontier AI research
- Real ownership and visible impact
- Technical depth paired with human interaction
- Fast feedback loops and high leverage
- There are very few roles that combine this level of technical rigor, customer proximity, and research exposure.